• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.6
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• pp.625-633
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• 2014

Mark III CCS plate is considered in this paper to perform its strength assessment. Mark III CCS plate is designed and constructed by stacking various non-metallic engineering materials such as plywood, triplex and reinforced PU foam that are supported by series of mastic upon inner steel hull structure. From the viewpoint of structural analysis, this plated structure is treated as a laminated anisotropic structure. Commercially available general purpose finite element analysis programs such as MSC PATRAN and MARC are used to develop the finite element (FE) model of the Mark III CCS plate. Because of the characteristics of LNG cargo that the Mark III CCS plate deals with, it is subjected to a wide range of temperature variations, i.e. about $-163^{\circ}C$ to $20^{\circ}C$. Different material properties of the Mark III CCS plate at these temperature levels are considered in the FE model. Using the developed FE model, strength assessment procedure is developed incorporating various anisotropic failure criteria such as Hashin, Hill, Hoffman, Maximum stress and Tsai-Wu. The strength assessment is performed within the initial failure state of the Mark III CCS plate and, as a result, failure details such as failure locations and loads are identified.

• International Journal of Quality Innovation
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• v.7 no.2
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• pp.141-156
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• 2006

This study describes a novel algorithm for optimizing the quality yield of silicon wafer slicing. 12 inch wafer slicing is the most difficult in terms of semiconductor manufacturing yield. As silicon wafer slicing directly impacts production costs, semiconductor manufacturers are especially concerned with increasing and maintaining the yield, as well as identifying why yields decline. The criteria for establishing the proposed algorithm are derived from a literature review and interviews with a group of experts in semiconductor manufacturing. The modified Delphi method is then adopted to analyze those results. The proposed algorithm also incorporates the analytic hierarchy process (AHP) to determine the weights of evaluation. Additionally, the proposed algorithm can select the evaluation outcomes to identify the worst machine of precision. Finally, results of the exponential weighted moving average (EWMA) control chart demonstrate the feasibility of the proposed AHP-based algorithm in effectively selecting the evaluation outcomes and evaluating the precision of the worst performing machines. So, through collect data (the quality and quantity) to judge the result by AHP, it is the key to help the engineer can find out the manufacturing process yield quickly effectively.